time-to-botec

Benchmark sampling in different programming languages
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README.md (4160B)

      1 <!--
      2 
      3 @license Apache-2.0
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      5 Copyright (c) 2018 The Stdlib Authors.
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      7 Licensed under the Apache License, Version 2.0 (the "License");
      8 you may not use this file except in compliance with the License.
      9 You may obtain a copy of the License at
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     11    http://www.apache.org/licenses/LICENSE-2.0
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     13 Unless required by applicable law or agreed to in writing, software
     14 distributed under the License is distributed on an "AS IS" BASIS,
     15 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
     16 See the License for the specific language governing permissions and
     17 limitations under the License.
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     19 -->
     20 
     21 # incrmda
     22 
     23 > Compute the [mean directional accuracy][mean-directional-accuracy] (MDA) incrementally.
     24 
     25 <section class="intro">
     26 
     27 The [mean directional accuracy][mean-directional-accuracy] is defined as
     28 
     29 <!-- <equation class="equation" label="eq:mean_directional_accuracy" align="center" raw="\operatorname{MDA} = \begin{cases} 1 & \textrm{if}\ N = 1 \\\frac{1}{N} \sum_{i=1}^{N} \delta_{\operatorname{sgn}(\Delta f_{i,i-1}),\ \operatorname{sgn}(\Delta a_{i,i-1})} & \textrm{if}\ N > 1 \end{cases}" alt="Equation for the mean directional accuracy."> -->
     30 
     31 <div class="equation" align="center" data-raw-text="\operatorname{MDA} = \begin{cases} 1 & \textrm{if}\ N = 1 \\\frac{1}{N} \sum_{i=1}^{N} \delta_{\operatorname{sgn}(\Delta f_{i,i-1}),\ \operatorname{sgn}(\Delta a_{i,i-1})} & \textrm{if}\ N > 1 \end{cases}" data-equation="eq:mean_directional_accuracy">
     32     <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@95b364439921fe28429acff89c5ba464a5a60caf/lib/node_modules/@stdlib/stats/incr/mda/docs/img/equation_mean_directional_accuracy.svg" alt="Equation for the mean directional accuracy.">
     33     <br>
     34 </div>
     35 
     36 <!-- </equation> -->
     37 
     38 where `f_i` is the forecast value, `a_i` is the actual value, `sgn(x)` is the [signum][@stdlib/math/base/special/signum] function, and `δ` is the [Kronecker delta][@stdlib/math/base/special/kronecker-delta]. 
     39 
     40 </section>
     41 
     42 <!-- /.intro -->
     43 
     44 <section class="usage">
     45 
     46 ## Usage
     47 
     48 ```javascript
     49 var incrmda = require( '@stdlib/stats/incr/mda' );
     50 ```
     51 
     52 #### incrmda()
     53 
     54 Returns an accumulator `function` which incrementally computes the [mean directional accuracy][mean-directional-accuracy].
     55 
     56 ```javascript
     57 var accumulator = incrmda();
     58 ```
     59 
     60 #### accumulator( \[f, a] )
     61 
     62 If provided input values `f` and `a`, the accumulator function returns an updated [mean directional accuracy][mean-directional-accuracy]. If not provided input values `f` and `a`, the accumulator function returns the current [mean directional accuracy][mean-directional-accuracy].
     63 
     64 ```javascript
     65 var accumulator = incrmda();
     66 
     67 var m = accumulator( 2.0, 3.0 );
     68 // returns 1.0
     69 
     70 m = accumulator( -1.0, 4.0 );
     71 // returns 0.5
     72 
     73 m = accumulator( -3.0, -2.0 );
     74 // returns ~0.67
     75 
     76 m = accumulator();
     77 // returns ~0.67
     78 ```
     79 
     80 </section>
     81 
     82 <!-- /.usage -->
     83 
     84 <section class="notes">
     85 
     86 ## Notes
     87 
     88 -   Input values are **not** type checked. If provided `NaN` or a value which, when used in computations, results in `NaN`, the accumulated value is `NaN` for **all** future invocations. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function.
     89 
     90 </section>
     91 
     92 <!-- /.notes -->
     93 
     94 <section class="examples">
     95 
     96 ## Examples
     97 
     98 <!-- eslint no-undef: "error" -->
     99 
    100 ```javascript
    101 var randu = require( '@stdlib/random/base/randu' );
    102 var incrmda = require( '@stdlib/stats/incr/mda' );
    103 
    104 var accumulator;
    105 var v1;
    106 var v2;
    107 var i;
    108 
    109 // Initialize an accumulator:
    110 accumulator = incrmda();
    111 
    112 // For each simulated datum, update the mean directional accuracy...
    113 for ( i = 0; i < 100; i++ ) {
    114     v1 = ( randu()*100.0 ) - 50.0;
    115     v2 = ( randu()*100.0 ) - 50.0;
    116     accumulator( v1, v2 );
    117 }
    118 console.log( accumulator() );
    119 ```
    120 
    121 </section>
    122 
    123 <!-- /.examples -->
    124 
    125 <section class="links">
    126 
    127 [mean-directional-accuracy]: https://en.wikipedia.org/wiki/Mean_Directional_Accuracy_%28MDA%29
    128 
    129 [@stdlib/math/base/special/signum]: https://www.npmjs.com/package/@stdlib/math-base-special-signum
    130 
    131 [@stdlib/math/base/special/kronecker-delta]: https://www.npmjs.com/package/@stdlib/math-base-special-kronecker-delta
    132 
    133 </section>
    134 
    135 <!-- /.links -->